1.
Online Offender’s Database
Structure and Analyses
By Geoffrey Mwedde (WCS)
at the Tackling Wildlife Crime Differently
Workshop
Held 5th April 2017 at Protea Hotel Kampala

2.
Outline
• Background
• Overview of the offenders’ database
• Why the online offenders’ database?
• Sample analyses

3.
UWA’s law enforcement budget
• Between 45-95% of UWA’s
budget is invested in law
enforcement at any site
they manage.
• Need to measure
effectiveness of this
expenditure and look at
ways it can be improved
• Tools developed to capture
data to enable this to
happen

4.
MIST and SMART
• UWA developed MIST in
1998
• Tested and updated in
Murchison Falls National
Park
• WCS helped UWA roll it
out to all PAs from 2001
• Taken around World
• SMART partnership
developed to update MIST
and provide more analysis
capabilities
• www.smartconservationsoftwa

5.
Changing patrol coverage
Kibale National Park, Uganda
LEM was implemented in Kibale
National Park in 2004 and as patrol
coverage maps were produced
wardens started to orient patrols
to areas that had been rarely
patrolled if at all.
2004 2005 2006 2007
2008 2009 2013

6.
Limits to MIST/SMART data
• Tools captured data from
Patrols including arrests –
can map arrest locations and
summarise basic data on
arrests
• However, did not track
suspects well nor what
happened to them in the
courts
– Often treated as first time
offenders because no record of
previous arrests

7.
Fingerprint option

8.
Why an online database?
• Increasing need for
Intelligence information
to tackle wildlife crime
and trafficking
• Intelligence tools like I2
and Sentinel are useless
without data
• Need data in real time
and ability to update
regularly

9.
Important intelligence data
• Telephone number of suspect
– Can link to records of calls made by others
– Can check address where registered
• Village location and parish (ideally with GPS location
in case follow up needed)
– Can check hotspots of people involved in wildlife crime
• Associates
– Who works together – partners may provide links to
middlemen

10.
Law enforcement and court cases
– Able to track repeat offenders and retrieve records for
court
– Able to track and document of court cases and verdict
– Map hotspots – A GIS (ESRI) Analysis has been
incorporated
commercial hunting
– MFNP & QENP

11.
Structure of offenders’ database
• Three main tables:
– Suspects
– Arrests
– Court cases
• Two analysis options
– Summary queries – automatic and
results produced on screen and as
.csv file
– Export data and analyse
independently

12.
Getting the online database to work
• Needs leadership from Protected Area Authority
Headquarters – someone needs to push to make sure
all sites collect and enter data
• While fairly simple to use there is a need to train in
its use as staff move on and are replaced
• Need a dedicated computer – part of problem with
slow take up in UWA
• Internet connection can be frustrating in Africa –
dongles are a good alternative and cost $10/month
to top up with data

13.
Data sheets for offline data storage
• Created data sheets for
Suspects, arrests and
court cases
• Allows data to be
collected if in a rush
and then entered later
• Also ensures paper
record which can be
signed by suspect which
may be useful for future
prosecutions

14.
Offline data entry package developed

15.
Types of analyses that can be made with
offenders’ database data
• Summary queries by Protected Area between
specific dates:
– Numbers of arrests and number of offenders
– Number of first, second, third+ time offenders
– Summed numbers and weight of evidence impounded
– Total fines, prison terms and community service days
– Average fine, prison term or community service days for
first time or repeat offenders
– Number of prosecutions and percentage successful

16.
Arrests over time

17.
Time of day arrests made

18.
Detection of offender

19.
Reasons for arrests

20.
Repeat offender frequency

21.
Verdicts

22.
Percentage of successful prosecutions

23.
Penalties per crime type

24.
Trend in fines

25.
Trends in prison terms

26.
Comparison of Courts

27.
Acknowledgements
• Andy Plumptre/Wildlife Conservation Society
• Uganda Wildlife Authority
• IWT

28.
THANK YOU!